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test_cdr.py
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test_cdr.py
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# Copyright (C) 2021 Unitary Fund
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
"""Tests for the Clifford data regression top-level API."""
import pytest
from typing import List
import numpy as np
import cirq
from cirq import LineQubit
from mitiq import PauliString, Observable, QPROGRAM
from mitiq._typing import SUPPORTED_PROGRAM_TYPES
from mitiq.cdr import (
execute_with_cdr,
linear_fit_function_no_intercept,
linear_fit_function,
mitigate_executor,
cdr_decorator,
)
from mitiq.interface import convert_from_mitiq, convert_to_mitiq
from mitiq.cdr._testing import random_x_z_cnot_circuit
from mitiq.interface.mitiq_cirq import compute_density_matrix
# Allow execution with any QPROGRAM for testing.
def execute(circuit: QPROGRAM) -> np.ndarray:
return compute_density_matrix(convert_to_mitiq(circuit)[0])
def batched_execute(circuits) -> List[np.ndarray]:
return [execute(circuit) for circuit in circuits]
def simulate(circuit: QPROGRAM) -> np.ndarray:
return compute_density_matrix(
convert_to_mitiq(circuit)[0], noise_level=(0,)
)
@pytest.mark.parametrize("circuit_type", SUPPORTED_PROGRAM_TYPES.keys())
@pytest.mark.parametrize(
"fit_function", [linear_fit_function, linear_fit_function_no_intercept]
)
@pytest.mark.parametrize(
"kwargs",
[
{},
{
"method_select": "gaussian",
"method_replace": "gaussian",
"sigma_select": 0.5,
"sigma_replace": 0.5,
},
],
)
@pytest.mark.parametrize("random_state", [1, 2, 3, 4, 5])
def test_execute_with_cdr(circuit_type, fit_function, kwargs, random_state):
circuit = random_x_z_cnot_circuit(
LineQubit.range(2),
n_moments=5,
random_state=random_state,
)
circuit = convert_from_mitiq(circuit, circuit_type)
obs = Observable(PauliString("XZ"), PauliString("YY"))
true_value = obs.expectation(circuit, simulate)
noisy_value = obs.expectation(circuit, execute)
cdr_value = execute_with_cdr(
circuit,
execute,
obs,
simulator=simulate,
num_training_circuits=20,
fraction_non_clifford=0.5,
fit_function=fit_function,
random_state=random_state,
**kwargs,
)
assert abs(cdr_value - true_value) <= abs(noisy_value - true_value)
@pytest.mark.parametrize("circuit_type", SUPPORTED_PROGRAM_TYPES.keys())
@pytest.mark.parametrize(
"fit_function", [linear_fit_function, linear_fit_function_no_intercept]
)
@pytest.mark.parametrize(
"kwargs",
[
{},
{
"method_select": "gaussian",
"method_replace": "gaussian",
"sigma_select": 0.5,
"sigma_replace": 0.5,
},
],
)
@pytest.mark.parametrize("random_state", [1, 2, 3, 4, 5])
def test_decorator_execute_with_cdr(
circuit_type, fit_function, kwargs, random_state
):
obs = Observable(PauliString("XZ"), PauliString("YY"))
@cdr_decorator(
observable=obs,
simulator=simulate,
num_training_circuits=20,
fraction_non_clifford=0.5,
fit_function=fit_function,
random_state=random_state,
**kwargs,
)
def decorated_execute(circuit: QPROGRAM) -> np.ndarray:
return execute(circuit)
def decorated_execute_with_cdr(circuit_type):
circuit = random_x_z_cnot_circuit(
LineQubit.range(2),
n_moments=5,
random_state=random_state,
)
circuit = convert_from_mitiq(circuit, circuit_type)
true_value = obs.expectation(circuit, simulate)
noisy_value = obs.expectation(circuit, execute)
cdr_value = decorated_execute(
circuit,
)
assert abs(cdr_value - true_value) <= abs(noisy_value - true_value)
def decorated_execute_using_clifford_circuit():
a, b = cirq.LineQubit.range(2)
clifCirc = cirq.Circuit(
cirq.H.on(a),
cirq.H.on(b),
)
cdr_mitigaged = decorated_execute(clifCirc)
assert obs.expectation(clifCirc, simulate) == cdr_mitigaged
decorated_execute_with_cdr(circuit_type)
decorated_execute_using_clifford_circuit()
@pytest.mark.parametrize("circuit_type", SUPPORTED_PROGRAM_TYPES.keys())
@pytest.mark.parametrize(
"fit_function", [linear_fit_function, linear_fit_function_no_intercept]
)
@pytest.mark.parametrize(
"kwargs",
[
{},
{
"method_select": "gaussian",
"method_replace": "gaussian",
"sigma_select": 0.5,
"sigma_replace": 0.5,
},
],
)
@pytest.mark.parametrize("random_state", [1, 2, 3, 4, 5])
def test_mitigated_execute_with_cdr(
circuit_type, fit_function, kwargs, random_state
):
circuit = random_x_z_cnot_circuit(
LineQubit.range(2),
n_moments=5,
random_state=random_state,
)
circuit = convert_from_mitiq(circuit, circuit_type)
obs = Observable(PauliString("XZ"), PauliString("YY"))
true_value = obs.expectation(circuit, simulate)
noisy_value = obs.expectation(circuit, execute)
cdr_executor = mitigate_executor(
executor=execute,
observable=obs,
simulator=simulate,
num_training_circuits=20,
fraction_non_clifford=0.5,
fit_function=fit_function,
random_state=random_state,
**kwargs,
)
cdr_mitigated = cdr_executor(circuit)
assert abs(cdr_mitigated - true_value) <= abs(noisy_value - true_value)
cdr_batched_executor = mitigate_executor(
executor=batched_execute,
observable=obs,
simulator=simulate,
num_training_circuits=20,
fraction_non_clifford=0.5,
fit_function=fit_function,
random_state=random_state,
**kwargs,
)
cdr_batched_mitigated_values = cdr_batched_executor([circuit] * 3)
assert [
abs(cdr_batched_mitigated - true_value)
<= abs(noisy_value - true_value)
for cdr_batched_mitigated in cdr_batched_mitigated_values
]
@pytest.mark.parametrize("circuit_type", SUPPORTED_PROGRAM_TYPES.keys())
def test_execute_with_variable_noise_cdr(circuit_type):
circuit = random_x_z_cnot_circuit(
LineQubit.range(2), n_moments=5, random_state=1
)
circuit = convert_from_mitiq(circuit, circuit_type)
obs = Observable(PauliString("IZ"), PauliString("ZZ"))
true_value = obs.expectation(circuit, simulate)
noisy_value = obs.expectation(circuit, execute)
vncdr_value = execute_with_cdr(
circuit,
execute,
obs,
simulator=simulate,
num_training_circuits=10,
fraction_non_clifford=0.5,
scale_factors=[1, 3],
random_state=1,
)
assert abs(vncdr_value - true_value) <= abs(noisy_value - true_value)
@pytest.mark.parametrize("circuit_type", SUPPORTED_PROGRAM_TYPES.keys())
def test_mitigate_executor_with_variable_noise_cdr(circuit_type):
circuit = random_x_z_cnot_circuit(
LineQubit.range(2), n_moments=5, random_state=1
)
circuit = convert_from_mitiq(circuit, circuit_type)
obs = Observable(PauliString("IZ"), PauliString("ZZ"))
true_value = obs.expectation(circuit, simulate)
noisy_value = obs.expectation(circuit, execute)
vncdr_executor = mitigate_executor(
executor=execute,
observable=obs,
simulator=simulate,
num_training_circuits=10,
fraction_non_clifford=0.5,
scale_factors=[1, 3],
random_state=1,
)
mitigated = vncdr_executor(circuit)
assert abs(mitigated - true_value) <= abs(noisy_value - true_value)
def test_no_num_fit_parameters_with_custom_fit_raises_error():
with pytest.raises(ValueError, match="Must provide `num_fit_parameters`"):
execute_with_cdr(
random_x_z_cnot_circuit(
LineQubit.range(2), n_moments=2, random_state=1
),
execute,
observables=Observable(PauliString()),
simulator=simulate,
fit_function=lambda _: 1,
)
def test_no_num_fit_parameters_mitigate_executor_raises_error():
with pytest.raises(ValueError, match="Must provide `num_fit_parameters`"):
mitigated_executor = mitigate_executor(
executor=execute,
observables=Observable(PauliString()),
simulator=simulate,
fit_function=lambda _: 1,
)
mitigated = (
mitigated_executor(
random_x_z_cnot_circuit(
LineQubit.range(2), n_moments=2, random_state=1
)
),
)
mitigated
def test_execute_with_cdr_using_clifford_circuit():
a, b = cirq.LineQubit.range(2)
clifCirc = cirq.Circuit(
cirq.H.on(a),
cirq.H.on(b),
)
obs = Observable(PauliString("XZ"), PauliString("YY"))
cdr_value = execute_with_cdr(
clifCirc, observable=obs, executor=execute, simulator=simulate
)
assert obs.expectation(clifCirc, simulate) == cdr_value
def test_mitigate_executor_with_cdr_using_clifford_circuit():
a, b = cirq.LineQubit.range(2)
clifCirc = cirq.Circuit(
cirq.H.on(a),
cirq.H.on(b),
)
obs = Observable(PauliString("XZ"), PauliString("YY"))
mitigated_executor = mitigate_executor(
observable=obs, executor=execute, simulator=simulate
)
mitigated = mitigated_executor(clifCirc)
assert obs.expectation(clifCirc, simulate) == mitigated